We define a swarm's robustness along two axes: (1) ability to collectively
adapt to temporally varying levels of sensor and actuator noise, and (2) ability
to collectively adapt to temporal changes in the swarm size. Both of these axes are
well motivated in real world examples, such as underwater environments, mining, and
distribution warehouses [1]}, [2]}, [3]}, [4]}, [5]}.
In such environments, swarms may have to deal with one or more of: (1) high levels of
sensor and actuator noise, (2) adversarial task re-allocation in which robots can
leave a sub-swarm working on a certain task at any time, and (3) frequent robot
mechanical failures.
